Hardware Profiling: The target hardware can be profiled in real-time by running sampled models on the actual target device (hardware-in-the-loop), estimated using lookup tables or prediction models, or analytically estimated using architectural heuristics. Common hardware profiling techniques are shown in Table REF  Hardware-in-the-loop is slowest but most accurate during NAS runtime, while analytical estimation is fastest but least accurate [1]}[2]}. Examples of analytical models for microcontrollers include using FLOPS as a proxy for latency [3]}[4]}, and standard RAM usage model [5]} for working memory estimation. Recently, latency prediction models have been made more accurate through kernel (execution unit) detection and adaptive sampling [6]}.
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